• DocumentCode
    248753
  • Title

    Temporal depth video enhancement based on intrinsic static structure

  • Author

    Lu Sheng ; King Ngi Ngan ; Songnan Li

  • Author_Institution
    Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Hong Kong, China
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    2893
  • Lastpage
    2897
  • Abstract
    Depth video enhancement is an essential preprocessing step for various 3D applications. Despite extensive studies of spatial enhancement, effective temporal enhancement that both strengthens temporal consistency and keeps correct depth variation needs further research. In this paper, we propose a novel method to enhance the depth video by blending raw depth frame with the estimated intrinsic static structure, which defines static structure of captured scene and is estimated iteratively by a probabilistic generative model with sequentially incoming depth frames. Our experimental results show that the proposed method is effective both in static and dynamic scene and is compatible with various kinds of depth videos. We will demonstrate that superior performance can be achieved in comparison with existing temporal enhancement approaches.
  • Keywords
    image enhancement; probability; video signal processing; depth variation correction; dynamic scene; intrinsic static structure; probabilistic generative model; raw depth frame; spatial enhancement; static scene; temporal depth video enhancement approach; Approximation methods; Cameras; Estimation; Joints; Parameter estimation; Probabilistic logic; Reliability; depth video enhancement; probabilistic model; temporal enhancement; variational approximation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025585
  • Filename
    7025585